Analyzing large datasets has become a common activity in many industrial fields. Generally, datasets are acquired from internal and/or external sources as quantitative data, which can be used in statistical analyses to support accurate and timely business decisions. In some cases, a dataset is too large to visualize and analyze each data point individually. In such cases, users can cluster the data, thus simplifying the analysis and the visualization of the entire dataset.
Complex datasets, including spatial and temporal variant data, cannot always be clustered according to a fixed rule. When processing complex datasets histograms can be applied to analyze data distribution and to identify existing clusters. Therefore, using an interactive visualization tool based on histograms can support users in identifying clusters and outliers in large and complex datasets.